Yihua Zhang


Room 3210

428 S Shaw LN

East Lansing, Michigan

United States of America

I am Yihua Zhang (张逸骅), a second-year Ph.D. student from OPTML Group at Michigan State University, supervised by Prof. Sijia Liu. My research focuses on the trustworthy and scalable ML algorithms. In general, my research spans the areas of machine learning (ML)/deep learning (DL), optimization theory, computer vision, and security. These research topics provide a solid foundation for my current and future research: Making AI system responsible and efficient. My research on these two goals are intervened and can be summarized as the following two perspectives:

:heavy_check_mark: Algorithmic perspective: This line of research designs the scalable and theoretically-grounded machine learning algorithms subject to real-life constraints, e.g., computation/communication overhead, robustness, fairness, and interpretability.

:heavy_check_mark: Application perspective: This line of research tackles the domain-specific challenges to achieve scalable and trustworthy AI, e.g., robustness enhancement, fairness promotion, data privacy protection, and model compression.


May 19, 2023 :tada: I am honored to be selected to be the CVPR 2023 Outstanding Reviewer (232/7000+)!
Apr 24, 2023 :tada: One paper accepted in ICML 2023!
Apr 24, 2023 :jack_o_lantern: Call for papers for 2nd New Frontiers in Adversarial Machine Learning and I will serve as the student chair!
Feb 27, 2023 :new_moon_with_face: One first-authored paper rejected by CVPR’23! :tada: One fourth-authored paper accepted by CVPR’23!
Feb 9, 2023 :tada: Our AAAI’23 tutorial on Bi-level Optimization in ML: Foundations and Applications is now available!

First-Authored Publications

See a full publication list at here.

  1. ICLR’23
    What Is Missing in IRM Training and Evaluation? Challenges and Solutions
    Yihua Zhang, Pranay Sharma, Parikshit Ram, Mingyi Hong, Kush Varshney, and Sijia Liu
    In Eleventh International Conference on Learning Representations 2023
  2. NeurIPS’22
    Advancing Model Pruning via Bi-level Optimization
    Yihua Zhang*, Yuguang Yao*, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, and Sijia Liu
    In Thirty-sixth Conference on Neural Information Processing Systems 2022
  3. NeurIPS’22
    Fairness Reprogramming
    Guanhua Zhang*, Yihua Zhang*, Yang Zhang, Wenqi Fan, Qing Li, Sijia Liu, and Shiyu Chang
    In Thirty-sixth Conference on Neural Information Processing Systems 2022
  4. ICML’22
    Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization
    Yihua Zhang*, Guanhua Zhang*, Prashant Khanduri, Mingyi Hong, Shiyu Chang, and Sijia Liu
    In Proceedings of the 39th International Conference on Machine Learning 2022
  5. CVPR’22
    Quarantine: Sparsity Can Uncover the Trojan Attack Trigger for Free
    Tianlong Chen*, Zhenyu Zhang*, Yihua Zhang*, Shiyu Chang, Sijia Liu, and Zhangyang Wang
    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2022